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An Evolutionary Algorithm-Based Approach for Classification Rule Discovery

Author

Listed:
  • Basheer M Al Maqaleh
  • Mohammed A Al Dhobai
  • Mohammed Y Magnam

Abstract

Automated discovery of classification rules is an active research area of significant importance as the discovered rules improve the decision-making process in various real world situations across a wide spectrum of application fields. This paper presents a classification algorithm based on Evolutionary Algorithm (EA) for mining classification rules from large database in the form ‘If P Then D’. A flexible encoding scheme, genetic operators and a suitable fitness function to measure the goodness of rules are proposed for effective evolution of rule sets. Experimental result shows that the EA proposed in this paper is suitable for classification rule mining and those rules discovered by the algorithm have higher classification performance to unknown data.

Suggested Citation

  • Basheer M Al Maqaleh & Mohammed A Al Dhobai & Mohammed Y Magnam, 2012. "An Evolutionary Algorithm-Based Approach for Classification Rule Discovery," The IUP Journal of Knowledge Management, IUP Publications, vol. 0(4), pages 7-13, October.
    • Handle: RePEc:icf:icfjkm:v:10:y:2012:i:3:p:7-14
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